• DocumentCode
    3576785
  • Title

    Applied cognitive psychology in software debugging process to predict software reliability growth

  • Author

    Kuei-Chen Chiu

  • Author_Institution
    Res. Center for Value-Added Health Data Anal. & Applic., Nat. Cheng Kung Univ., Tainan, Taiwan
  • fYear
    2014
  • Firstpage
    1399
  • Lastpage
    1403
  • Abstract
    This study applied cognitive psychology in software testing/debugging process to predict software reliability by the time lag between error-detection and error-renovation. This paper integrates the SRGMs of Chiù et al. using the time-varying learning effects [2] to measure the performance of error-detection and error-renovation in a software testing/debugging project for the datasets in Huang & Hung [8], this study also figure out the time lag between error-detection and error-renovation with time-varying learning effects and predict software reliability growth by the time lag. According to the results, the software testing/debugging managers can master the remaining time to remove errors and lift software reliability to the goal ahead of time based on errors-detection rate by improve learning effects. The results will help software system testing/debugging managers to shorten software testing time, save testing time, dominate the market by releasing software system ahead of time, and manage the software testing/debugging process more efficiently.
  • Keywords
    cognition; program debugging; program testing; psychology; software development management; software reliability; SRGMs; applied cognitive psychology; error detection; error renovation; software debugging process; software reliability growth prediction; software testing process; time-varying learning effects; Debugging; Fitting; Mathematical model; Predictive models; Silicon compounds; Software reliability; Software testing; Software reliability growth models; Time-varying Learning Effects; cognitive learning; performance management; time lag;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management (IEEM), 2014 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/IEEM.2014.7058868
  • Filename
    7058868